143 resultados para EXTRACTION COLUMNS


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The invention relates to a process for dissolving metals (e.g., Al, Cu, Fe, Cr, Sb, Ti, and W) in perhalide contg. ionic liqs. having the formula (I), and to the extn. of metals from mineral ores; the remediation of materials contaminated with heavy, toxic, or radioactive metals; and to the removal of heavy and toxic metals from hydrocarbon streams. In the formula (I), [X] comprises at least one perhalide anion selected from [I3]-, [BrI2]-, [Br2I]-, [ClI2]-, [ClBr2]-, [BrCl2]-, or [ICl2]-, [ClI3]-. The (Cat+) is a cationic species selected from: ammonium, azaannulenium, azathiazolium, benzimidazolium, benzofuranium, benzotriazolium, borolium, cinnolinium, diazabicyclodecenium, diazabicyclononenium, diazabicyclo- undecenium, dithiazolium, furanium, guanidinium, imidazolium, indazolium, indolinium, indolium, morpholinium, oxaborolium, oxaphospholium, oxazinium, oxazolium, iso-oxazolium, oxathiazolium, pentazolium, phospholium, phosphonium, phthalazinium, piperazinium, piperidinium, pyranium, pyrazinium, pyrazolium, pyridazinium, pyridinium, pyrimidinium, pyrrolidinium, pyrrolium, quinazolinium, quinolinium, isoquinolinium, quinoxalinium, selenozolium, sulfonium, tetrazolium, iso-thiadiazolium, thiazinium, thiazolium, thiophenium, thiuronium, triazadecenium, triazinium, triazolium, iso-triazolium, and uronium. [on SciFinder(R)]

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There is provided a process for the extn. of at least one arom. compd. from a mixt. with at least one aliph. hydrocarbon, which process comprises contacting said mixt. with a salt that is in a liq. state at a temp. below 150°C, said salt having a cation which comprises an arom. nitrogen-contg. heterocyclic ring system, in which a nitrogen atom forming part of said ring system is quaternized and in which said ring system is substituted by at least one electron-withdrawing substituent. Some of said salts are novel. [on SciFinder(R)]

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Sheep on the island of North Ronaldsay (Orkney, UK) feed mostly on seaweed, which contains high concentrations of dimethylated arsenoribosides. Wool of these sheep contains dimethylated, monomethylated and inorganic arsenic, in addition to unidentified arsenic species in unbound and complexed form. Chromatographic techniques using different separation mechanisms and detectors enabled us to identify five arsenic species in water extracts of wool. The wool contained 5.2 ± 2.3 μg arsenic per gram wool. About 80% of the arsenic in wool was extracted by boiling the wool with water. The main species is dimethylarsenic, which accounted for about 75 to 85%, monomethylated arsenic at about 5% and the rest is inorganic arsenic. Depending on the separation method and condition, the chromatographic recovery of arsenic species was between 45% for the anion exchange column, 68% for the size exclusion chromatography (SEC) and 82% for the cation exchange column. The SEC revealed the occurrence of two unknown arsenic compounds, of which one was probably a high molecular mass species. Since chromatographic recovery can be improved by either treating the extract with CuCl/HCl (CAT: 90%) or longer storage of the sample (CAT: 105%), in particular for methylated arsenic species, it can be assumed that labile arsenic -protein-like coordination species occur in the extract, which cannot be speciated with conventional chromatographic methods. It is clear from our study of sheep wool that there can be different kinds of 'hidden' arsenic in biological matrices, depending on the extraction, separation and detection methods used. Hidden species can be defined as species that are not recordable by the detection system, not extractable or do not elute from chromatographic columns. Copyright © 2003 John Wiley & Sons, Ltd.

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Existing studies have shown conclusively that the measured fibre reinforced polymer (FRP) rupture strain in FRP wrapped concrete columns is usually significantly smaller than the rupture strain obtained from flat coupon tests. One of the main causes for this phenomenon is the existence of geometrical discontinuities at both ends of the FRP sheets. This study proposes a new strengthening method in which continuous FRP spiral wrapping is used to eliminate strain concentrations due to the geometrical discontinuities and thus increase the FRP rupture strain at column failure. The effect of the spiral angle of FRP on the FRP rupture strain in FRP wrapped specimens was experimentally investigated. The test results indicate that the spiral wrapping with a small angle with respect to the column circumference can significantly increase the strain efficiency of FRP and thus enhance the axial compression capacity of the strengthened cylinders.

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The present invention relates to a novel class of water compatible molecularly imprinted polymers (AquaMIPs) capable of selectively binding target molecules such as riboflavin, or analogues thereof, in water or aqueous media, their synthesis and use thereof in food processing and extraction or separation processes.

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Glibenclamide (GLIB), an oral antidiabetic medication of the sulphonylurea drugs family, was stoichiometrically imprinted using tetrabutylammonium methacrylate as the functional monomer, for the first time in molecular imprinting, and utilising the sulphonylurea affinity for carboxylate anions. Solution association between the drug and the novel functional monomer was studied by 1H-NMR titrations, whereby evidence of sulphonylurea deprotonation followed by the formation of “narcissistic” GLIB dimers was found when tested in CDCl3, while an affinity constant in excess of 105 L mol-1 was measured in DMSO-d6. Detailed analysis of GLIB binding on the subsequently prepared imprinted and non-imprinted polymers confirmed deactivation of binding sites by exchange of a proton between GLIB and methacrylate, followed by extraction of the tetrabutylammonium counterion from the polymer matrix, resulting in overall reduced binding capacities and affinities by the imprinted material under equilibrium conditions. An optimised MI-SPE protocol, which included a binding site re-activation step, was developed for the extraction of GLIB from blood serum, whereby recoveries of up to 92.4% were obtained with exceptional sample clean-up.

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This paper uses the history of rubber extraction to explore competing attempts to control the forest environments of Assam and beyond in the second half of the nineteenth century. Forest communities faced rival efforts at environmental control from both European and Indian traders, as well as from various centres of authority within the Raj. Government attempts to regulate rubber collection were undermined by the weak authority of the Raj in these regions, leading to widespread smuggling. Partly in response to the disruptive influence of rubber traders on the frontier, the Raj began to restrict the presence of outsiders in tribal regions, which came to be understood as distinct areas outside British control. When rubber yields from the forests nearest the Brahmaputra fell in the wake of intensive exploitation, India's scientific foresters demanded and from 1870 obtained the ability to regulate the Assamese forests, blaming indigenous rubber tapping strategies for the declining yields and arguing that Indian rubber could be ‘equal [to] if not better' than Amazonian rubber if only tappers would change their practices. The knowledge of the scientific foresters was fundamentally flawed, however, and their efforts to establish a new type of tapping practice failed. By 1880, the government had largely abandoned attempts to regulate wild Indian rubber, though wild sources continued to dominate the supply of global rubber until after 1910.

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Reinforced concrete (RC) jacketing is a common method to retrofit existing columns with poor structural performance. It can be applied in two different ways: if the continuity of the jacket is ensured, the axial load of the column can be transferred to the jacket, which will be directly loaded; conversely, if no continuity is provided, the jacket induces only confinement action. In both cases the strength and ductility evaluation is rather complex, due to the different physical phenomena included, such as confinement, composite action core-jacket, preload, buckling of longitudinal bars.
Although different theoretical studies have been carried out to calculate the confinement effects, a practical approach to evaluate the flexural capacity and ductility is still missing. The calculation of these quantities is often related to the use of commercial computer programs, taking advantage of numerical methods such as fiber method or finite element method.
This paper presents a simplified approach to calculate the flexural strength and ductility of square RC jacketed sections subjected to axial load and bending moment. In particular the proposed approach is based on the calibration of the stress-block parameters including the confinement effect. Equilibrium equations are determined and buckling of longitudinal bars is modeled with a suitable stress-strain law. Moment-curvature curves are derived with simple calculations. Finally, comparisons are made with numerical analyses carried out with the code OpenSees and with experimental data available in the literature, showing good agreement.

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In many applications, and especially those where batch processes are involved, a target scalar output of interest is often dependent on one or more time series of data. With the exponential growth in data logging in modern industries such time series are increasingly available for statistical modeling in soft sensing applications. In order to exploit time series data for predictive modelling, it is necessary to summarise the information they contain as a set of features to use as model regressors. Typically this is done in an unsupervised fashion using simple techniques such as computing statistical moments, principal components or wavelet decompositions, often leading to significant information loss and hence suboptimal predictive models. In this paper, a functional learning paradigm is exploited in a supervised fashion to derive continuous, smooth estimates of time series data (yielding aggregated local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The proposed Supervised Aggregative Feature Extraction (SAFE) methodology can be extended to support nonlinear predictive models by embedding the functional learning framework in a Reproducing Kernel Hilbert Spaces setting. SAFE has a number of attractive features including closed form solution and the ability to explicitly incorporate first and second order derivative information. Using simulation studies and a practical semiconductor manufacturing case study we highlight the strengths of the new methodology with respect to standard unsupervised feature extraction approaches.

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In the catalytic hydrogenation of benzene to cyclohexane, the separation of unreacted benzene from the product stream is inevitable and essential for an economically viable process. In order to evaluate the separation efficiency of ionic liquids (ILs) as a solvent in this extraction processes, the ternary (liquid + liquid) equilibrium of 1-alkyl-3-methylimidazolium hexafluorophosphate, [Cnmim][PF6] (n = 4, 5, 6), with benzene and cyclohexane was studied at T = 298.15 K and atmospheric pressure. The reliability of the experimentally determined tie-line data was confirmed by applying the Othmer–Tobias equation. The solute distribution coefficient and solvent selectivity for the systems studied were calculated and compared with literature data for other ILs and sulfolane. It turns out that the benzene distribution coefficient increases and solvent selectivity decreases as the length of the cation alkyl chain grows, and the ionic liquids [Cnmim][PF6] proved to be promising solvents for benzene–cyclohexane extractive separation. Finally, an NRTL model was applied to correlate and fit the experimental LLE data for the ternary systems studied.

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Separation of benzene and cyclohexane is one of the most important and difficult processes in the petrochemical industry, especially for low benzene concentration. In this work, three ionic liquids (ILs), [Bmim][BF 4], [Bpy][BF 4], and [Bmim][SCN], were investigated as the solvent in the extraction of benzene from cyclohexane. The corresponding ternary liquid-liquid equilibria (LLE) were experimentally determined at T = 298.15 K and atmospheric pressure. The LLE data were correlated with the nonrandom two-liquid model, and the parameters were fitted. The separation capabilities of the ILs were evaluated in terms of the benzene distribution coefficient and solvent selectivity. The effect of the IL structure on the separation was explained based on a well-founded physical model, COSMO-RS. Finally, the extraction processes were defined, and the operation parameters were analyzed. It shows that the ILs studied are suitable solvents for the extractive separation of benzene and cyclohexane, and their separation efficiency can be generally ranked as [Bmim][BF 4] > [Bpy][BF 4] > [Bmim][SCN]. The extraction process for a feed with 15 mol % benzene was optimized. High product purity (cyclohexane 0.997) and high recovery efficiency (cyclohexane 96.9% and benzene 98.1%) can be reached. © 2012 American Chemical Society.

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Learning or writing regular expressions to identify instances of a specific
concept within text documents with a high precision and recall is challenging.
It is relatively easy to improve the precision of an initial regular expression
by identifying false positives covered and tweaking the expression to avoid the
false positives. However, modifying the expression to improve recall is difficult
since false negatives can only be identified by manually analyzing all documents,
in the absence of any tools to identify the missing instances. We focus on partially
automating the discovery of missing instances by soliciting minimal user
feedback. We present a technique to identify good generalizations of a regular
expression that have improved recall while retaining high precision. We empirically
demonstrate the effectiveness of the proposed technique as compared to
existing methods and show results for a variety of tasks such as identification of
dates, phone numbers, product names, and course numbers on real world datasets